Class 9 Demo - Introduction to Suitability

Thematic Criteria Layers > Suitability

Concepts & Themes:

This week’s lab will feature exploration of the following:

  1. MCE suitability using constraints and opportunities model
  2. Vector vs Raster suitability tools

Suitability - Constraints & Opportunities

The following suitability lab is designed to ascertain locations for potential parkland in Berkeley, CA based on MCE evaluation utilizing a Constraints & Opportunities analysis model. The MCE for both is as follows:

  • Constraints:

    • Avoid Toxic waste sites | toxic sites 500’ proximity - outside
    • Avoid high crime areas } crime 500’ proximity - outside
    • Avoid existing public parks
    • Avoid steep slopes | slope > 20% unacceptable
    • Avoid Geologic Hazards - landslides | landslides 200’ proximity - outside
    • Avoid Geologic Hazards - liquefaction | liquefaction - 100’ proximity - outside
    • Avoid shaded aspect | aspect north unacceptable
    • Avoid current parkland | parks .25 miles (1300) from existing - outside

  • Opportunities:

    • Close to population centers | census - 500’ from pop density > 15K
    • Close to Youth populations | census 500’ from <18 age that is greater than 5k density
    • Close to Elderly populations | census 500’ from >65 that is greater than 5k density
    • Minor or no slope | slope < 10%
    • Southerly aspects | aspect south - ideal
    • Easy access to transportation | streets 100’ from existing streets

C9 Steps:

Step #1:

  • Download the c9 demo data folder
  • Preview the data - opportunities, constraints and the project boundary
  • Connect QGIS to the data folder:

Suitability Data Inputs

Step #2:

  • Create two layer groups - one for opportunities and one for constraints importing the vector layers into their respective groups:

Opportunities + Constraints

  • Note that all project data is located in an established .prj:

Successful Cartographic Model requires consistent .prj

  • Establish project area (City of Berkeley boundary)

  • layers for the lab have been clipped to City of Berkeley boundary already for expediency:

  • Constraints:

    • aspect_con
    • crime_con
    • landslide_con
    • liquef_con
    • park_con
    • slope_con
    • toxic_con

Constraints

  • Opportunities:

    • under_18_opp
    • streets_opp
    • slope_opp
    • over_65_opp
    • hign_den_opp
    • aspect_opp

Opportunities

Step #3:

  • run proximity buffers per criteria for both constraints and opportunities

  • run slope per criteria constraints and opportunities

  • run aspect per criteria constraints and opportunities

  • Note: This step has already been enacted for expediency of the lab. The result of the criteria selections are vector features that fit criteria and have been weighted in the attribute table as either 1 for opportunities or -1 for constraints. In other words, each layer is equally weighted in this particular MCE analysis for parkland in Berkeley, CA as either 1 or -1

Step #4:

  • Typically overlay between two layers in suitability analysis can be conducted via UNION for both constraints and opportunities. The attribute table result will now feature a combination of all constraint or opportunity weights (-1) or (+1) per union polygon record. This will result in one layer for constraints and one layer for opportunities.

  • Save the UNION feature in an exports folder that you make within the l2_suit original download lab folder. Entitle the UNION Feature as opp_union.shp and con_union.shp respectively.

Step #5:

  • In the resulting opp_union.shp feature create new field total_opp

    • under_18_wt + aspect_wt + high_den_wt + over_65_wt + streets_wt + slope_wt

Union Opportunities

Step #6:

  • In the resulting con_union.shp feature create new field total_cons

  • Utilizing field calculator, add all constraint weights using the following equation (7 weight inputs):

    • aspect_wt + liquef_wt + crime_wt + slope_wt + toxic_wt + landsli_wt + park_wt

Union Constraints

Step #7:

  • Utilize the Delete Field tool to clean table of all attributes except total_opp and total_cons in their respective layers. Export the newly cleaned features as total_opp_clean and total_con_clean.

Step #8:

  • Utilizing total_opp_union.shp and total_con_union.shp as the inputs, a final suitablity map will be derived in this final lab step utilizing UNION:

Suitability Union

  • Suitability Map = Composite Constraint Map + Composite Opportunity Map

    • Export results as suitability.shp

    • Create new final column suitable in the suitability.shp

    • Utilize Field Calculator to add total_con + total_opp in the column suitable

    • Thematically map suitable column:

Score and Thematically Map Result

Step #9:

  • Discuss inclass further criteria that would refine the model to better fit real property in Berkeley, CA.

Step #10:

  • Rerun analysis in the raster model. To start, Rasterize the vector features, both opportunity and constraint themes via the total_con_clean and total_opp_clean inputs. Utilize the following parameters for each vector > raster run:

Rasterize Tool

Example showing Opportunity Input; run twice, second time for Constraint Input

  • burn-in value = weight value
  • Georeferenced units = 5 x 5
  • Output extent = B_Boundary
  • nodata value = Not Set
  • Int16 as number type

Step #11:

  • Review raster result:

Final Result can be Clipped to City Boundary